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When a data set is normally distributed about how much of the data fall within two standard deviations of the mean?
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Assume that aset of test scores is normally distributed with a mean of 100 and a standard deviation of 20 use the 68-95-99?
68% of the scores are within 1 standard deviation of the mean -80, 120 95% of the scores are within 2 standard deviations of the mean -60, 140 99.7% of the scores are within 3 standard deviations of the mean -40, 180
Why is it that only one normal distribution table is needed to find any probability under the normal curve?
Anything that is normally distributed has certain properties. One is that the bulk of scores will be near the mean and the farther from the mean you are, the less common the score. Specifically, about 68% of anything that is normally distributed falls within one standard deviation of the mean. That means that 68% of IQ scores fall between 85 and 115 (the mean being 100 and standard deviation being 15) AND 68% of adult male heights fall between 65 and 75 inches (the mean being 70 and I am estimating a standard deviation of 5). Basically, even though the means and standard deviations change, something that is normally distributed will keep these probabilities (relative to the mean and standard deviation). By standardizing these numbers (changing the mean to 0 and the standard deviation to 1) we can use one table to find the probabilities for anything that is normally distributed.
Statistic question help?
When using Chebyshev's Theorem the minimum percentage of sample observations that will fall within two standard deviations of the mean will be __________ the percentage within two standard deviations if a normal distribution is assumed Empirical Rule smaller than greater than the same as
What does it mean to have 95 percent confidence in an interval estimate?
It means that 95% of the values in the data set falls within 2 standard deviations of the mean value.
In statistics what does the empirical rule states?
Nearly all the values in a sample from a normal population will lie within three standard deviations of the mean. Please see the link.
Assume that aset of test scores is normally distributed with a mean of 100 and a standard deviation of 20 use the 68-95-99?
68% of the scores are within 1 standard deviation of the mean -80, 120 95% of the scores are within 2 standard deviations of the mean -60, 140 99.7% of the scores are within 3 standard deviations of the mean -40, 180
What is the measures that fall beyond three standard deviations of the mean called?
You may be referring to the statistical term 'outlier(s)'. Also, there is a rule in statistics called the '68-95-99 Rule'. It states that in a normally distributed dataset approximately 68% of the observations will be within plus/minus one standard deviation of the mean, 95% within plus/minus two standard deviations, and 99% within plus/minus three standard deviations. So if your data follow the classic bell-shaped curve, roughly 1% of the measures should fall beyond three standard deviations of the mean.
In a standard normal distribution 95 percent of the data is within plus standard deviations of the mean?
95% is within 2 standard deviations of the mean.
What percentage of the normally distributed population lies within the plus or minus one standard deviation of the population mean?
68.2%
What is the approximate percentage score of less than 140 using the 68-95-99.7 rule if a set of test scores is normally distributed with a mean of 100 and a standard deviation of 20?
The 68-95-99.7 rule states that in a normally distributed set of data, approximately 68% of all observations lie within one standard deviation either side of the mean, 95% lie within two standard deviations and 99.7% lie within three standard deviations.Or looking at it cumulatively:0.15% of the data lie below the mean minus three standard deviations2.5% of the data lie below the mean minus two standard deviations16% of the data lie below the mean minus one standard deviation50 % of the data lie below the mean84 % of the data lie below the mean plus one standard deviation97.5% of the data lie below the mean plus two standard deviations99.85% of the data lie below the mean plus three standard deviationsA normally distributed set of data with mean 100 and standard deviation of 20 means that a score of 140 lies two standard deviations above the mean. Hence approximately 97.5% of all observations are less than 140.
Why is it that only one normal distribution table is needed to find any probability under the normal curve?
Anything that is normally distributed has certain properties. One is that the bulk of scores will be near the mean and the farther from the mean you are, the less common the score. Specifically, about 68% of anything that is normally distributed falls within one standard deviation of the mean. That means that 68% of IQ scores fall between 85 and 115 (the mean being 100 and standard deviation being 15) AND 68% of adult male heights fall between 65 and 75 inches (the mean being 70 and I am estimating a standard deviation of 5). Basically, even though the means and standard deviations change, something that is normally distributed will keep these probabilities (relative to the mean and standard deviation). By standardizing these numbers (changing the mean to 0 and the standard deviation to 1) we can use one table to find the probabilities for anything that is normally distributed.
What percentage of scores fall within -3 and plus 3 standard deviations around the mean in a normal distribution?
99.7% of scores fall within -3 and plus 3 standard deviations around the mean in a normal distribution.
What percentage of a normal distribution is within 2 standard deviations of the mean?
I believe the standard deviations are measured from the median, not the mean.1 Standard Deviation is 34% each side of median, so that is 68% total.2 Standard Deviations is 48% each side of median, so that is 96% total.
What percentage of data would fall within 1.75 standard deviations of the mean?
About 81.5%
How much data is within 1.28 standard deviations of mean on bell shaped curve?
80%
Statistic question help?
When using Chebyshev's Theorem the minimum percentage of sample observations that will fall within two standard deviations of the mean will be __________ the percentage within two standard deviations if a normal distribution is assumed Empirical Rule smaller than greater than the same as
What is the proportion of the total area under the normal curve within plus or minus 2 standard deviations?
95%
